Grazia Caradonna

Improving the ANN Classification Accuracy of Landsat Data Through Spectral Indices and Linear Transformations (PCA and TCT) Aimed at LU/LC Monitoring of a River Basin

In this paper an efficient Artificial Neural Networks (ANN) classification method based on LANDSAT satellite data is proposed, studying the Cervaro river basin area (Foggia, Italy). LANDSAT imagery acquisition dates of 1984, 2003, 2009 and 2011 were selected to produce Land Use/Land Cover (LULC) maps to cover a time trend of 28 years. Land cover categories were chosen with the aim of characterizing land use according to the level of surface imperviousness. Nine synthetic bands from the PC, Tasseled Cap (TC), Brightness Temperature (BT) and vegetation indices (Leaf area Index LAI and the Modified Soil Adjusted Vegetation Index MSAVI) were identified as the most effective for the classification procedure. The advantages in using the ANN approach were confirmed without requiring a priori knowledge on the distribution model of input data. The results quantify land cover change patterns in the river basin area under study and demonstrate the potential of multitemporal LANDSAT data to provide an accurate and cost effective means to map and analyze land cover changes over time that can be used as input for subsequent hydrological and planning analysis.

The Use of Geomorphological Descriptors and Landsat-8 Spectral Indices Data for Flood Areas Evaluation: A Case Study of Lato River Basin

In the last few years, the scientific community has dedicated a strong effort for the rapid identification and mapping of flood risk. Last generation models have often taken advantage (even without of in-situ measurements) of the distributed information provided from remotely sensed data. In this work is proposed a multidisciplinary approach to reproduce maps of flooded areas. The method compared spectral descriptors to estimate the areas at risk of flooding in the Lato river basin (Puglia region - Southern Italy) using the ground effects caused by flood events. The inundated areas, obtained with a 2D hydraulic model, were used as reference for Landsat-8 spectral indices. The selection of the most appropriate spectral index was achieved using the binary classifiers test. Lastly, the adopted procedure provided also the calibration of different geomorphological descriptors for a rapid identification of areas at risk of flooding by using Digital Elevation Models.

Sharing Environmental Geospatial Data Through an Open Source WebGIS

In recent years, people’s need to participate to decision making, especially when it concerns inalienable human rights such as health and living in a healthy environment, has become increasingly manifest. In order to meet the request for environmental information sharing on the web and to make citizens feel “partakers” in the development of environmental policies, the Physical Agents Simple Operative Unit of ARPA Puglia, developed an open source WebGIS as a communication, participation and working tool for both Citizens and Technicians.

A Comparison of Low-Poly Algorithms for Sharing 3D Models on the Web

In recent years, the rising popularity of 3D models in the field of Cultural Heritage has brought additional geo-spatial formats for its documentation, making necessary to test new approaches in managing, publishing and studying heterogeneous data in an integrated way. Nowadays several computer applications and IT instruments are available for the management of cultural, archaeological and environmental heritages. The large size and complex nature of data makes it difficult for heritage experts to manage them for run more complex spatial analyses. Furthermore, it is also more difficult for citizens to access 3D models aimed at tourism and education. In this paper, we analyze recent low-poly methods aimed at reducing the size and complexity of 3D models applied to the case study of an historical building of Bari (Italy). The main idea is to create simple geometries (through low-poly algorithms) to significantly reduce the number of polygons in the reality-based environment and publish the model on the web. After the comparative evaluation of different low-poly algorithms and the generation of a test model, a PostgreSQL DBMS and a front-end PHP interface were developed to allow users to analyze and query the model.

Calibration of the CLAIR Model by Using Landsat 8 Surface Reflectance Higher-Level Data and MODIS Leaf Area Index Products

This study proposes a method for the calibration of the semi-empirical CLAIR model, a simplified reflectance model used to estimate Leaf Area Index (LAI) from optical data. The procedure can be applied in case of lacking of both LAI field measurements and surface reflectance data by exploiting free of charge data as the novel high level Landsat 8 Operational Land Imager Surface Reflectance (OLISR) product and the MODIS LAI (MCD15A3H level 4 product). This last dataset was used as LAI reference within an iterative procedure based on the resampling, at the MODIS pixel size, of LAI estimated from OLISR data. The procedure generated LAI information consistent with the MCD15A3H LAI estimation. Lastly, the method was tested and statistically assessed in a territory characterized by an extremely heterogeneous and fragmented landscape (irrigation district “Sinistra Ofanto”) located in the Apulia Region (Italy).

A Webgis Framework for Disseminating Processed Remotely Sensed on Land Cover Transformations

Abstract Mediterranean regions have experienced significant soil degradation over the past decades. In this context, careful land observation using satellite data is crucial for understanding the long-term usage patterns of natural resources and facilitating their sustainable management to monitor and evaluate the potential degradation. Given the environmental and political interest on this problem, there is urgent need for a centralized repository and mechanism to share geospatial data, information and maps of land change. Geospatial data collecting is one of the most important task for many users because there are significant barriers in accessing and using data. This limit could be overcome by implementing a WebGIS through a combination of existing free and open source software for geographic information systems (FOSS4G). In this paper we preliminary discuss methods for collecting raster data in a geodatabase by processing open multi-temporal and multi-scale satellite data aimed at retrieving indicators for land degradation phenomenon (i.e. land cover/land use analysis, vegetation indices, trend analysis, etc.). Then we describe a methodology for designing a WebGIS framework in order to disseminate information through maps for territory monitoring. Basic WebGIS functions were extended with the help of POSTGIS database and OpenLayers libraries. Geoserver was customized to set up and enhance the website functions developing various advanced queries using PostgreSQL and innovative tools to carry out efficiently multi-layer overlay analysis. The end-product is a simple system that provides the opportunity not only to consult interactively but also download processed remote sensing data.

Evaluation of relative radiometric correction techniques on Landsat 8 OLI sensor data

The quality of information derived from processed remotely sensed data may depend upon many factors, mostly related to the extent data acquisition is influenced by atmospheric conditions, topographic effects, sun angle and so on. The goal of radiometric corrections is to reduce such effects in order enhance the performance of change detection analysis. There are two approaches to radiometric correction: absolute and relative calibrations. Due to the large amount of free data products available, absolute radiometric calibration techniques may be time consuming and financially expensive because of the necessary inputs for absolute calibration models (often these data are not available and can be difficult to obtain). The relative approach to radiometric correction, known as relative radiometric normalization, is preferred with some research topics because no in situ ancillary data, at the time of satellite overpasses, are required. In this study we evaluated three well known relative radiometric correction techniques using two Landsat 8 - OLI scenes over a subset area of the Apulia Region (southern Italy): the IR-MAD (Iteratively Reweighted Multivariate Alteration Detection), the HM (Histogram Matching) and the DOS (Dark Object Subtraction). IR-MAD results were statistically assessed within a territory with an extremely heterogeneous landscape and all computations performed in a Matlab environment. The panchromatic and thermal bands were excluded from the comparisons.

Multi-image 3D Reconstruction: A Photogrammetric and Structure from Motion Comparative Analysis

Virtual Web Reconstruction of cultural heritage is one of the most interesting and innovative tool to preserve historical, architectural and artistic memory of many sites, particularly the ones prone to disappear, as well as to promote territories and tourism development. Recently, high-resolution 3D models are realized through improved technology and integration of survey techniques such as laser scanning and photogrammetry. However, the large and complex volume of 3D data makes difficult to access and handle them for either experts and citizens. In particular, the rendering of large 3D models may influence the performance of web publication and browsing. Considering this background, the goal of this paper is the comparison between the level of accuracy and realism of 3D models optimized using two different mesh simplification.